Machine Learning Based Modeling of Terahertz Communication Channels for 6G Systems

Terahertz (THz) band (0.1‐10 THz) is now considered as a strong candidate band for the prospective 6G communications due to its intrinsic massive bandwidth and data rate support. The advent of artificual intelligence (AI) and machine learning (ML) in the communications paradigm has recently surged. Various tutorials and survey works have been published within the past few years on applications of AI/ML in wireless communications as well as for self‐ intelligent network organization and management.

By getting trained from dynamic and uncertain channel environments, AI/ML‐based approaches will play a crucial role in design of THz communication systems, including channel modeling, channel estimation, beamforming, spectrum management etc. In this project, ML‐based algorithms will be employed for evaluation and modeling of the THz band communication data by anticipating the electromagnetic signal loss in a certain unknown channel.